The specific computational task we target for our approach is the Visual Storytelling task. The Visual Storytelling task is the task of computationally generating narrative text from sequences of images [1]}. Various neural network-based approaches have been explored for automatically constructing stories for the Visual Storytelling task [2]}, [3]}, [4]}. These methods for Visual Storytelling focus on capturing the directly observable. They do not focus on explicitly determining and representing what the story behind the images is beyond the directly observable, as humans do. When humans write stories for the visual storytelling task, they include a conceptual expanse outside of, but related to, that which they observe, with emotions, motivations, causal chains, etc. To reach these narrative evaluations beyond the directly observable, we believe a computational system that uses sensemaking and narrative coherence connections would be beneficial.
